Generation of Water Demand Time Series through Spline Curves

Abstract

A novel application of spline curves was developed for tracing average daily trends of water demand. These trends were used as input of a stochastic model to generate synthetic time series considering the number of water users as the main input parameter. Hermite polynomials were used for a piecewise interpolation of some known points of the daily trend which were obtained through reliable equations from the literature, whereas unknown points were deduced based on the mathematical properties of the demand pattern. Daily demand time series were generated for different time resolutions using a Monte Carlo approach based on a mixed probability distribution. Results were compared with real observed demand data to validate the effectiveness of the proposed approach, showing encouraging results.